Feature selection in quantitative structure-activity relationships.
A key component of building quantitative structure-activity relationship (QSAR) models is the selection of an appropriate set of molecular features or descriptors. Feature selection can affect the accuracy, stability and interpretability of a model. There are thousands of molecular descriptors currently available, and the selection of an appropriate descriptor set for a particular model can be a daunting task. While there are no absolute rules for selecting appropriate sets of descriptors, a number of recent publications describe automated methods for identifying optimal feature sets. This review provides an overview of a number of the methods described in these publications.
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